See my full publication list in google scholar.
2024
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Constrained Reinforcement Learning Under Model Mismatch
Zhongchang Sun, Sihong He, Fei Miao, and 1 more author
arXiv preprint arXiv:2405.01327, 2024
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Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments
Han Wang, Sihong He, Zhili Zhang, and 2 more authors
arXiv preprint arXiv:2405.19499, 2024
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Adaptive Uncertainty Quantification for Trajectory Prediction Under Distributional Shift
Huiqun Huang, Sihong He, and Fei Miao
arXiv preprint arXiv:2406.12100, 2024
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What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
Songyang Han, Sanbao Su, Sihong He, and 4 more authors
Transactions on Machine Learning Research (TMLR), 2024
2023
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A Robust and Constrained Multi-Agent Reinforcement Learning Electric Vehicle Rebalancing Method in AMoD Systems
Sihong He, Yue Wang, Shuo Han, and 2 more authors
In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
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Robust electric vehicle balancing of autonomous mobility-on-demand system: A multi-agent reinforcement learning approach
Sihong He, Shuo Han, and Fei Miao
In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
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Robust Multi-Agent Reinforcement Learning with State Uncertainty
Sihong He, Songyang Han, Sanbao Su, and 3 more authors
Transactions on Machine Learning Research (TMLR), 2023
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Data-Driven Distributionally Robust Electric Vehicle Balancing for Autonomous Mobility-on-Demand Systems Under Demand and Supply Uncertainties
Sihong He, Zhili Zhang, Shuo Han, and 5 more authors
IEEE Transactions on Intelligent Transportation Systems, 2023
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Robust Multi-Agent Reinforcement Learning Considering State Uncertainties
Sihong He, Songyang Han, Sanbao Su, and 3 more authors
AI4ABM Workshop at the International Conference on Learning Representations (ICLR), 2023
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A Robust and Constrained Multi-Agent Reinforcement Learning Method for Electric Vehicle Rebalancing in AMoD Systems
Sihong He, Yue Wang, Shuo Han, and 2 more authors
AI4ABM Workshop at the International Conference on Learning Representations (ICLR), 2023
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Uncertainty quantification of collaborative detection for self-driving
Sanbao Su, Yiming Li, Sihong He, and 4 more authors
IEEE International Conference on Robotics and Automation (ICRA), 2023
2022
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What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
Songyang Han, Sanbao Su, Sihong He, and 3 more authors
In ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2022
2021
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Data-driven distributionally robust optimization for vehicle balancing of mobility-on-demand systems
Fei Miao, Sihong He, Lynn Pepin, and 5 more authors
ACM Transactions on Cyber-Physical Systems, 2021
2020
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Data-driven distributionally robust electric vehicle balancing for mobility-on-demand systems under demand and supply uncertainties
Sihong He, Lynn Pepin, Guang Wang, and 2 more authors
In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020